If you receive an error related to quotas while running the Tabular Workflow for End-to-End AutoML, you might need to request a higher quota. To learn more, see View and manage quotas.
The following table shows the quotas we recommend you to set. We recommend
setting the quota values to a function of the number of concurrent
training jobs (num_concurrent_pipeline) and the number of CPUs in the
requested region. The recommended values are valid only if you are using the
default Compute Engine resource configuration for your workflow.
| Service | Quota | Recommendation |
|---|---|---|
| Compute Engine API | CPUs | num_concurrent_pipeline x 440 CPUs |
| Compute Engine API | Persistent Disk Standard (GB) | num_concurrent_pipeline x 5TB persistent disk |
| Vertex AI API | Restricted image training CPUs for N1/E2 machine types per region | num_concurrent_pipeline x 440 CPUs |
| Vertex AI API | Restricted image training total persistent disk SSD storage (GB) per region | num_concurrent_pipeline x 8TB persistent disk |
| Vertex AI API | Resource management (CRUD) requests per minute per region | num_concurrent_pipeline x 150 |
| Vertex AI API | Job or LRO submission requests per minute per region | num_concurrent_pipeline x 6 |